Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

access icon free Improved droop control based on virtual reactance for battery cycle life equalisation management in microgrid

  • Author(s): Tianpei Zhou 1, 2  and  Wei Sun 1
    • View affiliations
  • Source: Volume 12, Issue 14, 14 August 2018, p. 3435 – 3441
    DOI:  10.1049/iet-gtd.2017.1129 , Print ISSN 1751-8687, Online ISSN 1751-8695
© The Institution of Engineering and Technology
Received 22/07/2017, Accepted 06/05/2018, Revised 14/01/2018, Published 15/05/2018

In microgrid with distributed energy storage, the line reactance of each distributed energy resource (DER) is not same due to their different distance far from the loads. This will lead to the ageing rate of every battery to be not consistent. Some of the batteries first appear ageing, the rest of the battery also quickly ages if these ageing batteries are not replaced in time. This will eventually make the whole microgrid cannot work properly. To solve this problem, the idea is inspired by V-shape formation of a flock of birds. The equalisation of line reactance between each DER is achieved through adopting improved droop control based on virtual reactance, and the equalisation of the cycle life of batteries is achieved by weighted factor for power rating method based on hierarchical control. Compared with the method without virtual reactance control, the cycle life of batteries is extended by 80% after using the proposed method.

Inspec keywords: ageing; distributed power generation; battery management systems; battery storage plants; hierarchical systems; power generation control

Other keywords: V-shape formation; ageing batteries; ageing rate; power rating method; distributed energy storage; line reactance; weighted factor; DER; battery cycle life equalisation management; hierarchical control; improved droop control; virtual reactance; microgrid

Subjects: Distributed power generation; Control of electric power systems; Other power stations and plants; Multivariable control systems

References

    1. 1)
      • 3. Gao, Z., Yang, J.H., Ji, Y.: ‘AC/DC hybrid micro grid load distribution and DC voltage control’, Electr. Energy Manage. Technol., 2015, 30, (2), pp. 56–60.
    2. 2)
      • 11. Jing, L., Huang, X., Wu, X.Z.H.: ‘Research on improved microsource droop control method’, Trans. China Electrotech. Soc., 2014, 29, (2), pp. 145–152.
    3. 3)
      • 4. Wu, H.B., Sun, H.: ‘New improved prediction algorithm for state of charge of battery’, J. Electron. Meas. Instrum., 2010, 24, (11), pp. 993–998.
    4. 4)
      • 10. Khasawneh, H.J., IIIindala, M.S.: ‘Battery cycle life balancing in a microgrid through flexible distribution of energy and storage’, J. Power Sources, 2015, 100, (6), pp. 803–813.
    5. 5)
      • 5. Warner, N.A.: ‘Secondary life of automotive lithium ion batteries: an aging and economic analysis’, PhD thesis, The Ohio State University, 2013.
    6. 6)
      • 8. Millner, A.: ‘Modeling lithium ion battery degradation in electric vehicles’. Proc. Int. Conf. Innovative Technologies for an Efficient and Reliable Electricity Supply (CITRES), Waltham, MA, USA, September 2010, pp. 349–356.
    7. 7)
      • 13. Lin, H.W.: ‘Study on control strategy of distributed generation interface in autonomous microgrid’, PhD thesis, Yanshan University, 2013.
    8. 8)
      • 12. Bao, W., Hu, X.H., Li, G.H.: ‘An improved droop control strategy based on virtual impedance in islanded micro-grid’, Power Syst. Prot. Control, 2013, 41, (16), pp. 7–13.
    9. 9)
      • 2. Li, J.F., Wang, G., Li, W.G.: ‘A control strategy to smooth the power of wind and photovoltaic generation with hybrid energy storage systems’, J. Northeast Dianli Univ., 2014, 34, (5), pp. 32–38.
    10. 10)
      • 14. Liu, Z.H., Bao, W.: ‘Research on control strategy of synchronous voltage source converter based on complex virtual impedance in microgrid’, Modern Electric Power, 2014, 31, (4), pp. 60–65.
    11. 11)
      • 7. Peterson, S., Apt, J., Whitacre, J.: ‘Lithium ion battery cell degradation resulting from realistic vehicle and vehicle to grid utilization’, J. Power Sources, 2010, 95, (4), pp. 2385–2392.
    12. 12)
      • 6. Ning, G., White, R.E., Popov, B.N.: ‘A generalized cycle life model of rechargeable li-ion batteries’, Electrochem. Acta, 2006, 51, (2), pp. 2012–2022.
    13. 13)
      • 1. Xiang, Y., Wei, Z.W., Sun, Q., et al: ‘Life cycle cost based optimal configuration of battery energy storage system in distribution network’, Power Syst. Technol., 2015, 39, (1), pp. 264–270.
    14. 14)
      • 9. Guenther, C., Schott, B., Hennings, W., et al: ‘Model-based investigation of electric vehicle battery aging by means of vehicle-to-grid scenario simulations’, J. Power Sources, 2013, 98, (4), pp. 604–610.
    15. 15)
      • 16. Guerrero, J.M., Vasquez, J.C., Matas, J.: ‘Control strategy for flexible microgrid based on parallel line-interactive UPS systems’, IEEE Trans. Ind. Electron., 2009, 56, (3), pp. 726–736.
    16. 16)
      • 15. Matas, J., Castilla, M.: ‘Virtual impedance loop for droop controlled single-phase parallel inverters using a second-order general-integrator scheme’, IEEE Trans. Power Electron., 2010, 25, (12), pp. 2993–3002.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-gtd.2017.1129
Loading

Related content

content/journals/10.1049/iet-gtd.2017.1129
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
Print this page
This is a required field
Please enter a valid email address